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Publications

Found 29 results
Filters: Author is Napel, S.  [Clear All Filters]
2020
Quantitative imaging feature pipeline: a web-based tool for utilizing, sharing, and building image-processing pipelines, Mattonen, S. A., Gude D., Echegaray S., Bakr S., Rubin D. L., and Napel S. , J Med Imaging (Bellingham), Jul, Volume 7, Number 4, p.042803, (2020)
2018
Intratumoral Spatial Heterogeneity at Perfusion MR Imaging Predicts Recurrence-free Survival in Locally Advanced Breast Cancer Treated with Neoadjuvant Chemotherapy, Wu, J., Cao G., Sun X., Lee J., Rubin D. L., Napel S., Kurian A. W., Daniel B. L., and Li R. , Radiology, Jul, Volume 288, Number 1, p.26-35, (2018)
Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer, Wu, J., Li X., Teng X., Rubin D. L., Napel S., Daniel B. L., and Li R. , Breast Cancer Res, Sep 3, Volume 20, Number 1, p.101, (2018)
Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications, Zhou, M., Leung A., Echegaray S., Gentles A., Shrager J. B., Jensen K. C., Berry G. J., Plevritis S. K., Rubin D. L., Napel S., et al. , Radiology, Jan, Volume 286, Number 1, p.307-315, (2018)
Quantitative Image Feature Engine (QIFE): an Open-Source, Modular Engine for 3D Quantitative Feature Extraction from Volumetric Medical Images, Echegaray, S., Bakr S., Rubin D. L., and Napel S. , J Digit Imaging, Aug, Volume 31, Number 4, p.403-414, (2018)
A radiogenomic dataset of non-small cell lung cancer, Bakr, S., Gevaert O., Echegaray S., Ayers K., Zhou M., Shafiq M., Zheng H., Benson J. A., Zhang W., Leung A. N. C., et al. , Sci Data, Oct 16, Volume 5, p.180202, (2018)
2017
Adaptive local window for level set segmentation of CT and MRI liver lesions, Hoogi, A., Beaulieu C. F., Cunha G. M., Heba E., Sirlin C. B., Napel S., and Rubin D. L. , Med Image Anal, Apr, Volume 37, p.46-55, (2017)
A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound, Lekadir, K., Galimzianova A., Betriu A., M. Vila Del Mar, Igual L., Rubin D. L., Fernandez E., Radeva P., and Napel S. , IEEE J Biomed Health Inform, Jan, Volume 21, Number 1, p.48-55, (2017)
Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer, Wu, J., Li B. L., Sun X. L., Cao G. H., Rubin D. L., Napel S., Ikeda D. M., Kurian A. W., and Li R. J. , RadiologyRadiology, Nov, Volume 285, Number 2, p.401-413, (2017)
Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative (18)F FDG-PET/CT metrics, Minamimoto, R., Jamali M., Gevaert O., Echegaray S., Khuong A., Hoang C. D., Shrager J. B., Plevritis S. K., Rubin D. L., Leung A. N., et al. , Oncotarget, Aug 8, Volume 8, Number 32, p.52792-52801, (2017)
Predictive radiogenomics modeling of EGFR mutation status in lung cancer, Gevaert, O., Echegaray S., Khuong A., Hoang C. D., Shrager J. B., Jensen K. C., Berry G. J., Guo H. H., Lau C., Plevritis S. K., et al. , Sci Rep, Jan 31, Volume 7, p.41674, (2017)
2016
A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound, Lekadir, K., Galimzianova A., Betriu A., Vila M. D., Igual L., Rubin D., Fernandez E., Radeva P., and Napel S. , IEEE J Biomed Health Inform, Nov 22, (2016)
Intratumor Partitioning of Serial Computed Tomography and FDG Positron Emission Tomography Images Identifies High-Risk Tumor Subregions and Predicts Patterns of Failure in Non-Small Cell Lung Cancer After Radiation Therapy, Wu, J., Gensheimer M. F., Dong X., Rubin D. L., Napel S., Diehn M., Loo, Jr. B. W., and Li R. , Int J Radiat Oncol Biol Phys, Oct 1, Volume 96, Number 2S, p.S100, (2016)
Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study, Wu, J., Gensheimer M. F., Dong X., Rubin D. L., Napel S., Diehn M., Loo, Jr. B. W., and Li R. , Int J Radiat Oncol Biol Phys, Aug 1, Volume 95, Number 5, p.1504-12, (2016)
2015
Content-based image retrieval in radiology: analysis of variability in human perception of similarity, Faruque, J., Beaulieu C. F., Rosenberg J., Rubin D. L., Yao D., and Napel S. , J Med Imaging (Bellingham), Apr, Volume 2, Number 2, p.025501, (2015)
Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities, Itakura, H., Achrol A. S., Mitchell L. A., Loya J. J., Liu T., Westbroek E. M., Feroze A. H., Rodriguez S., Echegaray S., Azad T. D., et al. , Sci Transl Med, Sep 2, Volume 7, Number 303, p.303ra138, (2015)
2014
On combining image-based and ontological semantic dissimilarities for medical image retrieval applications, Kurtz, C., Depeursinge A., Napel S., Beaulieu C. F., and Rubin D. L. , Med Image AnalMed Image Anal, Oct, Volume 18, Number 7, p.1082-100, (2014)
A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations, Kurtz, C., Beaulieu C. F., Napel S., and Rubin D. L. , J Biomed Inform, Mar 12, (2014)
Predicting Visual Semantic Descriptive Terms From Radiological Image Data: Preliminary Results With Liver Lesions in CT, Depeursinge, A., Kurtz C., Beaulieu C., Napel S., and Rubin D. , IEEE Trans Med ImagingIEEE Trans Med Imaging, Aug, Volume 33, Number 8, p.1669-76, (2014)
2012
Automatic annotation of radiological observations in liver CT images, Gimenez, F., Xu J., Liu Y., Liu T., Beaulieu C., Rubin D., and Napel S. , AMIA Annu Symp Proc, Volume 2012, p.257-63, (2012)
Modeling Perceptual Similarity Measures in CT Images of Focal Liver Lesions, Faruque, J., Rubin D. L., Beaulieu C. F., and Napel S. , J Digit Imaging, Dec 20, (2012)
Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data--methods and preliminary results, Gevaert, O., Xu J., Hoang C. D., Leung A. N., Xu Y., Quon A., Rubin D. L., Napel S., and Plevritis S. K. , RadiologyRadiology, Aug, Volume 264, Number 2, p.387-96, (2012)
Prognostic PET 18F-FDG uptake imaging features are associated with major oncogenomic alterations in patients with resected non-small cell lung cancer, Nair, V. S., Gevaert O., Davidzon G., Napel S., Graves E. E., Hoang C. D., Shrager J. B., Quon A., Rubin D. L., and Plevritis S. K. , Cancer Research, Aug 1, Volume 72, Number 15, p.3725-34, (2012)
Quantifying the margin sharpness of lesions on radiological images for content-based image retrieval, Xu, J., Napel S., Greenspan H., Beaulieu C. F., Agrawal N., and Rubin D. , Med PhysMed Phys, Sep, Volume 39, Number 9, p.5405-18, (2012)
2011
Automated temporal tracking and segmentation of lymphoma on serial CT examinations, Xu, J., Greenspan H., Napel S., and Rubin D. L. , Med PhysMed Phys, Nov, Volume 38, Number 11, p.5879-86, (2011)
A Comprehensive Descriptor of Shape: Method and Application to Content-Based Retrieval of Similar Appearing Lesions in Medical Images, Xu, J., Faruque J., Beaulieu C. F., Rubin D. L., and Napel S. , J Digit Imaging, May 6, (2011)
Managing biomedical image metadata for search and retrieval of similar images, Korenblum, D., Rubin D. L., Napel S., Rodriguez C., and Beaulieu C. , J Digit Imaging, Aug, Volume 24, Number 4, p.739-48, (2011)
2010
Content-Based Image Retrieval in Radiology: Current Status and Future Directions, Akgul, C. B., Rubin D. L., Napel S., Beaulieu C. F., Greenspan H., and Acar B. , J Digit Imaging, Apr 8, (2010)
Imaging informatics: toward capturing and processing semantic information in radiology images, Rubin, D. L., and Napel S. , Yearb Med Inform, p.34-42, (2010)